A nonlinear proximal point algorithm is proposed in the setting of adaptive control. Based on the Bregman generalized distance induced by a convex function, forward nonorthogonal projections provide a more general approach to classic optimization algorithms. Convergence theorems are provided for the application of the Bregman algorithm to the adaptive control of both linear systems and nonlinear control-affine systems. It is shown that the proposed algorithm is particularly suited for adaptive control applications because it outperforms the gradient algorithm for on-line parameter estimation. Simulations on an autonomous underwater vehicle and a robotic manipulator show the benefits of the proposed adaptive control scheme when compared to the classic ones.
A Bregman nonlinear proximal point algorithm for adaptive control
2011
6 Seiten, 3 Bilder, 2 Tabellen, 18 Quellen
Aufsatz (Konferenz)
Datenträger
Englisch
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